Affiliations on Crossref

Insights from a roundtable on author affiliation metadata

Amanda French — Thu, 22 Jan 2026 00:00:00 +0000

It’s been said that Americans are unusual in tending to ask “Where do you work?” as an initial question upon introduction to a new acquaintance, indicating a perhaps unhealthy preoccupation with work as identity. But in the context of published research, “What is this author’s affiliation?” is a question of global importance that goes beyond just wanting to know the name – and perhaps prestige level – of the place a researcher works.

When collected, used, and analyzed at scale, data about author affiliations can provide intriguing insights about international collaboration trends, signal trust and lack of trust in particular research institutions, generate business intelligence for publishers, help universities track the work their researchers do, help funders demonstrate the impact of their funding, and much more.

In November we partnered with OA Switchboard to organize a roundtable on author affiliation metadata for the Crossref community, service and infrastructure providers, production vendors, data scientists, researchers, and librarians. We aimed to bring together scholarly information professionals with many diverse perspectives; ultimately, participants from more than 40 organizations joined the roundtable to share their experiences and their thoughts.

In focusing on a single type of metadata, we hoped to focus our discussions, as well. Similarly, in October the Barcelona Declaration on Open Research Information organized a roundtable on “Moving Funding Metadata Forward” in which it became clear that “improving the quality and coverage of funding metadata was on the agenda of many organisations and there was a strong interest in collaborating on practical next steps.”

While many of the issues and solutions discussed at both roundtables are similar, in the course of the author affiliation metadata roundtable we identified some unique challenges as well as benefits related to this particular flavor of information. In this blog post, I’ll share these insights.

Insights from presenters

I opened the roundtable with a brief introduction and a working definition of affiliation metadata: names and/or identifiers such as Research Organization Registry (ROR) IDs for organizations where research was conducted or with which authors and contributors are associated, usually officially, as in their place of employment.

Next, to create a shared context for discussion, we heard four presentations on the current state of author affiliation metadata, its importance, and Crossref’s ongoing initiative to enhance it automatically.

Nees Jan van Eck of Leiden University’s Center for Science and Technology Studies (CWTS) shared observations on the state of author affiliations from a preprint titled “Crossref as a source of open bibliographic metadata” that presents the findings of an analysis performed annually since 2021. Nees’s key points:

Crossref is a foundational data source for bibliographic metadata.
Affiliation metadata is available for only 1 out of 3 journal articles in Crossref for the period 2023-2024.
There is considerable variation in the extent to which Crossref members deposit affiliation metadata.
Downstream sources try to fill gaps using suboptimal approaches, leading to missing, inaccurate, and inconsistent linking of publications to institutions.
Publications lacking affiliation metadata in Crossref are less visible in bibliometric applications, analyses, studies, and tools (such as the open edition of the Leiden Ranking of over 2800 universities).

Next, Yvonne Campfens of OA Switchboard reiterated the desirability of the Crossref community providing complete and accurate author affiliation metadata at the source. Yvonne called upon publishers to “Integrate metadata creation in your systems and workflows before publication and relay it throughout the editorial, production, and publication processes.”

Yvonne pointed out that in the context of managing Open Access agreements, publishers ought to keep in mind that providing good affiliation metadata improves customer satisfaction, since institutions and consortia need to have that information in order to connect research to the correct organization. In closing, Yvonne featured best practices from OA Switchboard’s Data Quality Challenge:

eLife captures affiliations at submissions with “author select,” ensuring that ROR IDs are introduced early and verified before publication, coupled with a quality assurance process during proofing. (See also our piece on Metadata Excellence Award winner eLife.)
EMS Press captures metadata via manuscript extraction as early as at submission, building on globally valid identifiers whenever possible (ROR IDs, DOIs, ORCIDs).
Pensoft Publishers uses AI-assisted metadata extraction with human review and in-house metadata validation.
Beilstein-Institut performs post-acceptance metadata quality assurance through automation and expert review.
The Royal Society embeds metadata in OA payment and agreement workflows.
American Chemical Society (ACS) has a multi-method persistent identifier matching strategy with near-complete coverage.
The American Society for Microbiology (ASM) combines AI-powered submission tools with editorial oversight via expert manual checks. (See also our piece on Metadata Excellence Award winner ASM.)
Rockefeller University Press (RUP) maintains ROR IDs across the full publishing workflow with “author select” at submission through metadata deposits upon publication. (See also the ROR case study on RUP.)

Adam Day of Clear Skies Ltd began his talk by wryly framing the first and second rules of data science as contradictory: “Never fix data: always use sources that produce high-quality data in the first place,” but also “Get good at fixing data, because you will have to.” Adam went on to demonstrate the central role author affiliation metadata plays in research integrity investigations, displaying anonymized data for institutions with a high number of alerts. In conclusion, Adam reiterated the importance of author affiliation metadata to research integrity efforts:

Data analysis is critical to research integrity.
Quality data helps enormously by giving oversight, saving time, and assisting investigations.

Lastly, our own Director of Technology Dominika Tkaczyk gave an account of our plans to enrich author affiliation metadata by matching organization name text strings to ROR IDs as part of our metadata matching initiative. A strategy for performing such matching has already been developed and tested and an open dataset of results made available. Tests on a set of 3,000 affiliations sampled from our metadata show that the strategy can be expected to match 95 million ROR IDs to organization names with 97.35% precision, an astronomical increase over the less than 1 million ROR IDs deposited in Crossref records to date.

Dominika concluded the presentation portion of the session by reiterating that our planned enrichment of author affiliation metadata

Will use flexible and transparent matching strategies (and open code),
Will welcome community participation in developing new strategies, and
Will be available in the REST API.

Automatic matching of organization names to ROR IDs in author affiliations cannot solve the problem of missing organization names, of course, but it represents a huge leap forward in addressing metadata quality issues.

All of our speakers’ presentations are available on Zenodo at https://doi-org.pluma.sjfc.edu/10.13003/661591chqlyw.

Insights into challenges

In the next stage of the event, participants broke into six breakout groups to identify factors contributing to incomplete or inaccurate affiliation metadata. Participants were pre-assigned to groups randomly by role to ensure a variety of perspectives in every discussion.

At least two participants, it should be noted, pointed out that it would be helpful to agree on a definition of “complete” and “accurate” affiliation metadata, which in itself is a challenge, and one we did not address in this roundtable. For instance, practices most recently have trended away from defining a complete author affiliation in open metadata as including an institutional address, although many internal databases might include such information separately.

Even without such definitions, however, all six groups were able to identify several general areas for attention, and one participant provided a particularly helpful categorization of these areas that is largely reused here.

Inherent data complexity

Research organizations have names in different languages, abbreviations, and many other name variants.
Research organizations have frequent name changes, mergers, and rebranding.
Research organizations have different degrees, levels, and complexity of hierarchical granularity, and authors, publishers, and software systems are often misaligned as to which level in an organization’s structure is appropriate to use in a particular instance.
Research organizations often lack official policies on how affiliations should be written, leading to hundreds of variations for a single institution.

Corresponding authors often submit information for all co-authors, which can lead to inaccuracies.
Many authors have multiple profiles across multiple submission systems, which can introduce errors.
Authors may have “octopus affiliations,” claiming affiliations with many institutions that are difficult to verify.
Authors may fail to update affiliations when changing institutions between manuscript acceptance and publication.
Authors may demonstrate “apathy” when repeatedly filling out submission forms, sometimes providing incomplete, inconsistent, or incorrect information.
On occasion, authors might even provide false or purchased affiliations, which of course is a significant research integrity concern.

Technical barriers

Many manuscript tracking and peer review systems, especially legacy systems, lack structured fields for affiliations or don’t support open organization identifiers like ROR.
Some systems limit authors to a single affiliation, despite many researchers having multiple institutional connections.
Some systems only collect affiliation information for the corresponding author.
Some systems link affiliations to user accounts instead of to publications.
Different systems use competing identifier registries, including proprietary identifier registries, creating interoperability challenges.

Publisher practices

Even when publishers improve current metadata collection practices, historical data correction is resource-intensive and often not prioritized.
Publishers collect affiliation information at submission but don’t ensure that it is maintained throughout all stages of the publication process and deposited in metadata.
Some publishers are unaware of the importance of author affiliation metadata or do not prioritize its improvement.
Some publishers deliberately choose not to deposit affiliation metadata to Crossref, viewing it as value-added information they’ve invested in curating.

Insights into solutions

Naturally, we didn’t rest at identifying challenges: after a break, we gathered in the same groups to brainstorm approaches to improving author affiliation metadata.

Adopt collective approaches

Collective action, where corrections and improvements made by various stakeholders flow back into shared systems, has historically worked for proprietary systems and could be even more powerful with open infrastructure.
Since those who do not provide metadata “upstream” will inevitably have it provided for them “downstream” by multiple separate entities using multifarious methods, provenance metadata indicating who asserted author affiliations and how (whether automatically or with the author’s or editor’s input) would help metadata users assess trust levels.

Engage authors and institutions

Reach out to authors and institutions to educate them on the need for more consistent affiliation reporting, especially in terms of language, name format, and degree of hierarchical granularity.
Demonstrate the benefit to institutions of maintaining accurate records in registries like ROR, including abbreviations and name variants.
Publishers and/or software systems should allow authors to review (though not necessarily edit) affiliation information during the proofing process to verify accuracy. Authors should not, however, need to know, see, or use ROR IDs.

Improve the tech

Publishers would welcome submission systems that incorporate structured fields for author affiliations with well-designed auto-suggestions linked to ROR or other organization identifiers.
Making affiliation data mandatory at submission could significantly improve capture rates, although it would be important to ensure that independent researchers can use these systems as well.
Enable collection of affiliations for all authors, not just the corresponding author.
Pull in verified affiliation information from ORCID.
Increasingly, intelligent matching systems can be implemented to reduce author burden and perhaps also increase accuracy and completeness of metadata.
Better crosswalks between different organization identifier systems would make it vastly easier for publishers to maintain better metadata. Since open registries cannot include proprietary information, proprietary registries should provide their customers with crosswalks to all standard open identifiers.

Encourage publisher best practices

Publishers can use already-available tools to help assess and improve the quality of both new and legacy author affiliation metadata.
Share the benefits of improved author affiliation metadata for internal and external analytics, customer satisfaction, and research integrity.
Identify best practices in collecting and structuring author affiliation metadata.
Understand that the entire research ecosystem would benefit from publishers sharing collected affiliation data with Crossref.

It’s worth mentioning that these solutions are heterogeneous: not all strategies can be implemented by any one actor nor even by any one sector of our profession. Clearly, collaborative action is necessary for substantive change.

Moving forward

The affiliations metadata roundtable represented an important step in addressing affiliation metadata challenges in a productive and collaborative way. If there was a consensus, it was that while perfect completeness and accuracy of author affiliation metadata may not be achievable (or even definable), incremental improvements can substantially enhance the quality and availability of affiliation metadata for the entire scholarly information community.

Here at Crossref, we intend to use the insights from this roundtable to inform our support of the Crossref community, including publishers, service providers, and metadata users. We welcome your comments, questions, and suggestions on this issue! Share your thoughts with Amanda French at alfrench@crossref.org.

References

van Eck, N. J., & Waltman, L. (2025). Crossref as a source of open bibliographic metadata (No. smxe5_v2). MetaArXiv. https://doi-org.pluma.sjfc.edu/10.31222/osf.io/smxe5_v2
Tkaczyk, D. (2025). Crossref relationships involving research organisations [Dataset]. Zenodo. https://doi-org.pluma.sjfc.edu/10.5281/zenodo.15254993
French, A., van Eck, N. J., Campfens, Y., Day, A., & Tkaczyk, D. (2026, January 19). Affiliations Metadata Roundtable 2025—All Presentations. https://doi-org.pluma.sjfc.edu/10.13003/661591chqlyw

Participating organizations


Africa PID Alliance / TCC Africa	Frontiers Media SA
American Association of Cancer Research (AACR)	Iowa State
American Chemical Society (ACS)	Kriyadocs / Exeter Premedia Services
American Physical Society (APS)	MDPI
American Society for Microbiology (ASM)	Noyam Publishers
Aptara	OpenAIRE / OpenOrgs
Australian Research Data Commons (ARDC)	Optica Publishing Group
Atypon	ORCID
Beilstein-Institut	Oxford University Press
California Digital Library (CDL)	Public Knowledge Project (PKP)
Cambridge University Press	Public Library of Science (PLOS)
Carnegie Mellon University	River Valley Technologies
CHORUS	Rockefeller University Press
Clarivate / Web of Science	SAGE Publications
Copernicus GmBH	Barcelona Declaration on Open Research Information
Curtin University / Curtin Open Knowledge Initiative (COKI)	Silverchair / ScholarOne
De Gruyter Brill	Springer Science & Business
Digital Science / Figshare	TNQTech
Digital Science / Symplectic Elements	University of Laval
eLife	University of Chicago Press
Elsevier BV	University of Split
Enago

Some rip-RORing news for affiliation metadata

Ginny Hendricks — Mon, 26 Jul 2021 00:00:00 +0000

We’ve just added to our input schema the ability to include affiliation information using ROR identifiers. Members who register content using XML can now include ROR IDs, and we’ll add the capability to our manual content registration form, participation reports, and metadata retrieval APIs in the near future. And we are inviting members to a Crossref/ROR webinar on 29th September at 3pm UTC.

The background

We’ve been working on the Research Organization Registry (ROR) as a community initiative for the last few years. Along with the California Digital Library and DataCite, our staff has been involved in setting the strategy, planning governance and sustainability, developing technical infrastructure, hiring/loaning staff, and engaging with people in person and online. In our view, it’s the best current model of a collaborative initiative between like-minded open scholarly infrastructure (OSI) organisations.

Last year, Project Manager Maria Gould described the case for publishers adopting ROR and ROR was ranked the number one priority at our last in-person annual meeting. Now it’s time that Crossref’s services themselves took up the baton to meet the growing demand.

The inclusion of ROR in the Crossref metadata will help everyone in the scholarly ecosystem make critical connections more easily. For example, research institutions need to monitor and measure their output by the articles and other resources their researchers have produced. Journals need to know with which institutions authors are affiliated to determine eligibility for institutionally sponsored publishing agreements. Funders need to be able to discover and track the research and researchers they have supported. Academic librarians need to easily find all of the publications associated with their campus.

Earlier this month, GRID and ROR announced that after working together to seed the community-run Research Organization Registry, GRID would be retiring from public service and handing the proverbial torch over to ROR as the scholarly community’s reliable universal open identifier for affiliations. That means that our members who have been using GRID now need to consider their move to ROR and think about how they can add ROR IDs into the metadata that they manage and share through Crossref.

The plan

We’ve been able to include ROR IDs for our grant metadata schema as affiliation information for two years, since July 2019. And the Australia Research Data Commons (ARDC) was the first member to add ROR IDs to the Crossref system in 2020. In early July, we completed the work to accept ROR IDs for affiliation assertions for all other types of records with an affiliation or institution element, such as journal articles, book chapters, preprints, datasets, dissertations, and many more.

Next, we will commence the plans to support ROR in our other tools and services, such as Participation Reports. We’ll work on alignment with the Open Funder Registry and share our plans to collect the information via the new user interface we’re developing for registering and managing metadata. Open Journal Systems (OJS) already has a ROR Plugin, developed by the German National Library of Science and Technology (TIB). This supports the collection of ROR IDs and future releases of this plugin and the OJS DOI plugin will allow including ROR IDs in the metadata sent to Crossref, to support thousands of our members to share ROR IDs via their Crossref metadata. We also aim to add ROR to our metadata retrieval options, including the REST API, which recently saw the start of an unblocking with our move to a more robust technical foundation.

The call for participation

Many Crossref publishers, funders, and service providers are already planning to integrate ROR with their systems, map their affiliation data to ROR, and include ROR in Crossref metadata. In addition to publishers and funders, libraries, repositories, and other stakeholders are developing support for ROR. For example, the Plan S Journal Checker tool uses ROR IDs to let people check whether a particular journal is compliant with an author’s funder and institutional open access policies. In addition, the ROR website shows a growing list of active and in-progress ROR integrations.

Crossref members registering research grants via Altum’s ProposalCentral system can already add ROR IDs. Now those registering articles, books, preprints, datasets, dissertations, and other research objects, can start including much clearer and all-important affiliation metadata as part of their content registration going forward. As with all newly-introduced metadata elements, we recommend adding ROR IDs from now and ongoing, but planning a distinct project to backfill older records. We know that more than 80% of records have been updated and enriched at least once with additional and cleaner metadata, so as members do this routinely, they can include ROR IDs alongside updating URLs, license or funding information, and other metadata.

For information on how ROR will be supported in the Crossref metadata, take a look at our latest schema release (version 5.3.0) or in this journal article example XML.

Join the discussion in our forum below and register for the Crossref/ROR webinar on September 29th at 3pm UTC to learn all you need to know about incorporating ROR into your Crossref metadata.

Publishers, are you ready to ROR?

Maria Gould — Tue, 25 Aug 2020 00:00:00 +0000

If you manage a publishing system or workflow, you know how crucial—and how challenging!—it is to have clean, consistent, and comprehensive affiliation metadata. Author affiliations, and the ability to link them to publications and other scholarly outputs, are vital for numerous stakeholders across the research landscape. Institutions need to monitor and measure their research output by the articles their researchers have published. Funders need to be able to discover and track the research and researchers they have supported. Academic librarians need to easily find all of the publications associated with their campus. Journals need to know where authors are affiliated so they can determine eligibility for institutionally sponsored publishing agreements.

Until recently, an open, unambiguous, and persistent identifier for research organisation affiliations has been a missing layer of the scholarly ecosystem. DOIs could identify articles and datasets and other research outputs, and ORCID IDs could identify researchers, but no equivalent solution was available to identify institutions. With the launch of the Research Organization Registry (ROR) in 2019 (which Crossref has helped to develop), the landscape is changing. ROR IDs are an opportunity to make affiliation details easier for publishers to use and easier for those who rely on this data.

Affiliations are a key piece of Crossref metadata that has been missing, but will soon be supported in the Crossref metadata schema. This means that content registered with Crossref can be associated with a ROR IDs to enable better tracking and discovery of research and other publication outputs by institution.

What is ROR?

ROR is the Research Organization Registry––open, noncommercial, community-led infrastructure for research organisation identifiers. The registry currently includes globally unique persistent identifiers and associated metadata for more than 98,000 research organisations (as of August 2020).

ROR IDs are specifically designed to be implemented in any system that captures institutional affiliations and to enable connections (via persistent identifiers and networked research infrastructure) between research organisations, research outputs, and researchers.

ROR IDs are interoperable with those in other identifier registries, including GRID (which provided the seed data that ROR launched with), Crossref Funder Registry, ISNI, and Wikidata. ROR data is available under a CC0 waiver and can be accessed via a public API and data dump.

ROR is not the first organisation identifier to exist. But ROR is distinct because it is completely open, specifically focused on identifying affiliations, and collaboratively developed by, with, and for key stakeholders in scholarly communications. ROR is operated as a joint initiative by Crossref, DataCite, and California Digital Library, and was launched with seed data from GRID in collaboration with Digital Science. These organisations have invested resources into building an open registry of research organisation identifiers that can be embedded in scholarly infrastructure to effectively link research to organisations.

Why care about ROR IDs in Crossref metadata?

Ed Pentz, Crossref’s Executive Director, explains the key role ROR can play in enriching Crossref metadata:

“Over the years Crossref has expanded the metadata it collects (for example, ORCID IDs and license URLs) based on the changing needs of our members and the scholarly research community. A key type of metadata that is missing from Crossref is affiliations. We’ve had a lot of feedback from members that adding affiliations should be a priority. At Crossref LIVE19 in Amsterdam, ROR was ranked joint first place for Crossref by the 100 plus attendees at the meeting. For the last few years we’ve been diligently working on the initiative and are very happy that ROR is now coming to fruition.”

Crossref metadata does include some affiliations already. But this data is not comprehensive or consistent, and appears as free-text strings only (even if originally sourced from a list of institutions). A search for UC Berkeley, for instance, returns multiple variants of the university’s name:

University of California, Berkeley
University of California-Berkeley
University of California Berkeley
UC Berkeley
And likely more…

While it isn’t too difficult for a human to guess that “UC Berkeley,” “University of California, Berkeley,” and “University of California at Berkeley” are all referring to the same university, a machine interpreting this information wouldn’t necessarily make the same connections. If you are trying to easily find all of the publications associated with UC Berkeley, you would need to run and reconcile multiple searches at best, or miss data completely at worst. This is where an affiliation identifier comes in: a single, unambiguous, standardized identifier that will always stay the same (for UC Berkeley, that would be https://ror.org/01an7q238).

ROR IDs for affiliations can transform the usability of Crossref metadata. While it’s crucial to have IDs for affiliations, it’s equally important that the affiliation data can be easily used. The ROR dataset is CC0, so ROR IDs and associated affiliation data can be freely and openly used and reused without any restrictions.

What does this mean for publishers?

As the Crossref schema update is being cleared for takeoff, this is a good time for publishers and publishing service providers to be thinking about adopting ROR.

ROR IDs can be useful in publishing workflows in a variety of ways. They can easily be implemented into manuscript tracking systems to identify the affiliations of submitting authors and co-authors. This can be done via a simple institution lookup that connects to the ROR API. Authors choose their affiliation from a dropdown list populated from ROR; they do not have to provide a ROR ID or even know that a ROR ID is being collected.

Upon publication, ROR affiliation data can be included when content is registered with Crossref. ROR IDs are also supported in the JATS XML format that many publishers use. Crossref metadata can be searched and crawled, and the Crossref API will make ROR IDs available so affiliation data can be captured by tools and services and fed into downstream reporting and tracking systems.

Get ready to ROR!

ROR is already working with a number of publishers and service providers that are planning to integrate ROR in their systems, map their affiliation data to ROR IDs, and/or include ROR IDs in publication metadata.

For example: Rockefeller University Press has already added the collection of ROR IDs to their publication workflow. Upon submission, the author selects an institutional affiliation from a dropdown list of options that comes from ROR. Rockefeller University Press also relies on this affiliation data for billing and licensing purposes to coordinate Gold Open Access publishing agreements.

In addition to publishers, libraries and repositories and other stakeholders are building in support for ROR. You can also see the list of active and in-progress ROR integrations here.

We know decisions about identifier adoption aren’t easy or immediate, so get in touch with ROR if you have questions or want to be more involved in the project. ROR holds regular community meetings and webinars and supports several community working groups for those interested in implementing ROR IDs and working with ROR data. This is a community-driven effort so we want to hear from you!